The study, published in the journal Parkinsonism and Related Disorders, highlights a new approach that could significantly improve the early diagnosis of parkinsonism and other movement disorders.
It uses video analysis to assess motor symptoms by comparing movements on the left and right sides of the body, exploiting the “asymmetric onset” of Parkinson’s disease. The researchers used machine learning algorithms to carefully analyze videos of patients making simple movements with their arms and legs.
The study found that this method was 86% accurate in distinguishing healthy people from people with early-stage Parkinson’s disease.
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Source: Ferra
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